Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS‐CoV‐2 outbreak. Issue 4 (25th May 2020)
- Record Type:
- Journal Article
- Title:
- Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS‐CoV‐2 outbreak. Issue 4 (25th May 2020)
- Main Title:
- Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS‐CoV‐2 outbreak
- Authors:
- Bauer, Denis C.
Tay, Aidan P.
Wilson, Laurence O. W.
Reti, Daniel
Hosking, Cameron
McAuley, Alexander J.
Pharo, Elizabeth
Todd, Shawn
Stevens, Vicky
Neave, Matthew J.
Tachedjian, Mary
Drew, Trevor W.
Vasan, Seshadri S. - Abstract:
- Abstract: Pre‐clinical responses to fast‐moving infectious disease outbreaks heavily depend on choosing the best isolates for animal models that inform diagnostics, vaccines and treatments. Current approaches are driven by practical considerations (e.g. first available virus isolate) rather than a detailed analysis of the characteristics of the virus strain chosen, which can lead to animal models that are not representative of the circulating or emerging clusters. Here, we suggest a combination of epidemiological, experimental and bioinformatic considerations when choosing virus strains for animal model generation. We discuss the currently chosen SARS‐CoV‐2 strains for international coronavirus disease (COVID‐19) models in the context of their phylogeny as well as in a novel alignment‐free bioinformatic approach. Unlike phylogenetic trees, which focus on individual shared mutations, this new approach assesses genome‐wide co‐developing functionalities and hence offers a more fluid view of the 'cloud of variances' that RNA viruses are prone to accumulate. This joint approach concludes that while the current animal models cover the existing viral strains adequately, there is substantial evolutionary activity that is likely not considered by the current models. Based on insights from the non‐discrete alignment‐free approach and experimental observations, we suggest isolates for future animal models.
- Is Part Of:
- Transboundary and emerging diseases. Volume 67:Issue 4(2020)
- Journal:
- Transboundary and emerging diseases
- Issue:
- Volume 67:Issue 4(2020)
- Issue Display:
- Volume 67, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 67
- Issue:
- 4
- Issue Sort Value:
- 2020-0067-0004-0000
- Page Start:
- 1453
- Page End:
- 1462
- Publication Date:
- 2020-05-25
- Subjects:
- alignment‐free phylogeny -- bioinformatics -- COVID‐19 -- genomics -- PHEIC -- viral evolution
Veterinary medicine -- Periodicals
636.089 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1865-1682 ↗
http://www3.interscience.wiley.com/journal/118541580/home ↗
http://www.blackwell-synergy.com/rd.asp?goto=journal&code=jva ↗
https://www.hindawi.com/journals/schm/contents/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/tbed.13588 ↗
- Languages:
- English
- ISSNs:
- 1865-1674
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9020.570100
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20952.xml